MINING ENCRYPTED DATA

B. Boutsinas, G. C. Meletiou and M. N. Vrahatis
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B. Boutsinas: Department of Business Administration, University of Patras Artificial Intelligence Research Center (UPAIRC), University of Patras, GR-26500 Rio, Patras, Greece
G. C. Meletiou: T.E.I. of Epirus, P.O. Box 110, GR–47100 Arta and UPAIRC, Greece
M. N. Vrahatis: Department of Mathematics, UPAIRC, University of Patras, GR-26500 Patras, Greece

Chapter 16 in Supply Chain and Finance, 2004, pp 273-281 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractBusiness and scientific organizations, nowadays, own databases containing confidential information that needs to be analyzed, through data mining techniques, in order to support their planning activities. The need for privacy is imposed due to, either legal restrictions (for medical and socio-economic databases), or the unwillingness of business organizations to share their data which are considered as a valuable asset. Despite the diffusion of data mining techniques, the key problem of confidentiality has not been considered until very recently. In this chapter we address the issue of mining encrypted data, in order to both protect confidential information and to allow knowledge discovery. More specifically, we consider a scenario where a company having private databases negotiates a deal with a consultant. The company wishes the consultant to analyze its databases through data mining techniques. Yet the company is not willing to disclose any confidential information.

Keywords: Finance; Supply Chain; E-Commerce; Optimization; Mathematical Modeling; Operations Research (search for similar items in EconPapers)
Date: 2004
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